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E.W. Scripps School of Journalism PhD student Enakshi Roy shared in the top prize of the second annual Scripps Innovation Challenge, a media innovation contest sponsored by the Scripps College of Communication. She and Ehsan Ardjmand from Industrial Engineering and Naeem Gul from International Development studies split $10,000.

Roy writes, “We as a team . . . decided to solve the Challenge for Columbus Dispatch which was how do they monetize the 190,000 followers they have on Twitter. Using a data mining based algorithm, we came up with a software CATS — an acronym for Clustering, Audience Targeting and Shooting.”

The group used an algorithm to detect the communities for followers of a particular Twitter account. These communities are not demography based but rather based on who is following whom on Twitter and what their interests are. The team then uses a text mining algorithm to see what kind of words have a higher acceptance rate among these detected communities and then compose a Tweet with these “favorable” words.

Roy says, “Our assumption is, such Tweets will have a higher click rate leading to explicit or implicit monetization.”